Bo (Beth) Sun, Ph.D.
Associate Professor
Department of Computer Science, Rowan University
Research Interests: Visual Analytics, Data Visualization, Computer Vision and Simulation using Serious Gaming and Immersive Technologies
Biography
Dr. Sun currently is an associate professor in Department of Computer Science at Rowan University. She was also a visiting faculty at Center for Digital Visualization under Computer & Information Science Department at University of Pennsylvania. In 2016 and 2017, she worked as a guest/visiting scientist at Computer Science Initiative at Brookhaven National Lab. Before joining Rowan, she was former (interim) chair of Department of Computer Science at Lincoln University and respectively an assistant professor at Dept. of Bioinformatics and Computer Science in University of the Sciences. Dr. Sun's current research interests focus on Immersive Visual Analytics, an innovative way to analyze large scale and multi-dimensional dataset for big data using immersive technology. Her research interests also include Computer Vision and Simulation using Serious Gaming and Immersive Technologies. Dr. Sun is recipient of Best Post-Doc Presenter Award in The Siemens Post-Doctoral Workshop on Technology, Innovation & Entrepreneurship 2008 and her research is mainly supported by NSF, NIH and Department of Education.
Research Work
Visual Analytics to Explore Business Dataset
“A Visualization Study on Visual Analysis to Explore the Organizational Structure of the Group within a Factory”. Bo Sun, Ce Pang. IEEE Visualization and Computer Graphics, VAST Challenge, Berlin, German, Oct. 2018.
Given nine large scale datasets on communication between company employees, we conducted visual analytics to determine company growth and potential issues among employees.
Discover The Effect Of Chemical Release At Wildlife Preserve
“Using Tableau To Discover The Effect Of Chemical Release At Wildlife Preserve”. Bo Sun, Benjamin Weidner, Simon Su. IEEE Visualization and Computer Graphics, VAST Challenge, Berlin, German, Oct. 2018
Given large scale and temporal dataset on water sampling, we analyze the data to better understand the trends and anomalies that came with it. We also developed a prediction to what direction the rivers flow, and how each location is related to one another.
Immersive Visual Analytics to Explore Mystery at Wildlife Preserve
“Immersive Visual Analysis to Explore Mystery at Wildlife Preserve”. Aleksandr Fritz, Bo Sun, Wei Xu. IEEE Virtual Reality, Reutlingen, Germany, Mar. 2018. DOI: 10.1109/VR.2018.8446324
Given the large scale and multi-dimensional datasets on chemical releases, we develop immersive visual analytics to find the connections between manufactures and sensor readings, and eventually, to discover the potential reason of the bird decreasing
Video2.mov IEEE VR 3DUI contest: 3D User Interaction
“3DUI Contest 2018: 3D Interaction”, Bo Sun , Aleksandr Fritz, Simon Su, Vincent Perry and Paul Havig.IEEE Virtual Reality and 3DUI, 3DUI Contest, Reutlingen, Germany, Mar. 2018. DOI: 10.1109/VR.2018.8446176
We developed novel interactions to enable user interaction with the 3D virtual environment addressing the three tasks (Ladder Climbing, First-Person View Flying, and Tower Stacking) of the 3DUI contest 2018. Using Unity3D as our development environment, we implemented and deployed our application on HTC Vive HMD system.
IEEE VR 3DUI Submission.mp4Visual Analytics to Explore Mystery at Wildlife Preserve
“A Tableau Case Study On Visual Analysis To Explore Mystery At Wildlife Preserve”. Bo Sun, Rumeel Jessamy, Soogsoo Ha, Wei Xu. IEEE Visualization and Computer Graphics,VAST Challenge, Phoenix, AZ, Oct. 2017.
Given two large scale and multi-dimensional datasets on chemical release and meteorological information, we utilized Tableau visualization toolset to reveal the patterns of monitor observation and chemical release. Additionally, we developed a prediction method to connect the wind direction with the chemical release, which eventually suggests the release origins from surrounding manufactories
Tumor Vascular Permeability Measurement based on Color Image Analysis
“An Image Processing-Based Method For Quantification Of Microvasculature”. Bo Sun. 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) Chengdu, China, July 2014 pp. 1-6. doi:10.1109/ICMEW.2014.6890564.
Characteristic of microscopy vascular data is that it contains many tiny vessels with branching and complex structure. The quantification of these vascular network is crucial in diagnose of vascular abnormalities, surgical planning, and monitoring disease progress or remission. We developed an image processing method to automatically and accurately quantify the vessel. Two algorithms were developed here to isolate the pixels that represent the vessels. The first algorithm uses color ratios to segment vessels and the second helps compensate for light balance issues by breaking the image into segments.
Real-Time Sonography Simulation for Medical Training
"Real-Time Sonography Simulation for Medical Training". Bo Sun, Frederic D. McKenzie. International Journal of Education and Information Technologies, Issue 3 and Volume 5, 2011 (328-335).
We investigated a real time ultrasound simulation methodology based on 3-dimensional (3-D) mesh model of the organ. A virtual echocardiogram displays various sonograph orientation in real time according to the placement of a virtual transducer without the need of an actual patient.
MVI_0651.mpgPSTK: A Graphic Tool for Prostate Specimen Analysis and Visualization.
PSTK: A Graphic Tool for Prostate Specimen Analysis and Visualization. Bo Sun, Frederic D. McKenzie: IPCV 2010: Proceedings of the 2010 International Conference on Image Processing, Computer Vision, & Pattern Recognition, WORLDCOMP'10, July 12-15, 2010, Las Vegas Nevada, USA, Volume 2 (174-178).
Prostate Specimen Tool Kit (PSTK) allows surgeons to submit patient data and the system returns estimated analysis result and virtual segmentation solution for guiding future surgery. Here, we are presenting a first prototype of PSTK, a graphic tool for visually and numerically displaying the coverage results of excised prostate specimens.
An Augmented Reality System for Expanding Abnormalities of Standardized Patients
An Augmented Reality System for Expanding Abnormalities of Standardized Patients, Bo Sun, Frederic D. McKenzie. 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, Virginia, September 2006. (http://dx.doi.org/10.2514/6.2006-6900)
Standardized patients (SPs), individuals who realistically portray patients, are widely used in medical education to teach and assess students’ skill in communicating with patient, eliciting a history and performing a physical exam. Our research using augmented reality technology allows the learner to view an abnormal virtual 3D heart on a normal SP’s body in our simulated echocardiogram.
Gaze Tracking
The project aims to develop a visual tracking method to monitor eye movement in cognitive neuroscience using computer vision techniques. The tracking method will perform face recognition, particularly identifying gaze to record its movement, and meanwhile record a subject’s point of gaze during a given visual task.
LearningExpress App
The project focuses on providing an independent and affordable app to enhance student mastery of class subjects. The motivation for the app comes from recent literature and personal experience that indicate that students of color and women are less likely to participate in class. As a result, teachers may assume these students are not engaged in the material, so students may lose interest in the subject. Each application will be designed with multiple levels and include a tutorial, sample problems that provide the answer with an explanation, and practice problems of varying degrees of difficulty.
Published abstract: http://www.lugreat.com/ihe/pdfs/2015abs.pdf
Paper regarding similar app: http://ieeexplore.ieee.org/abstract/document/7753765/?reload=true